awesome-ml-pipelines and awesome-ml-monitoring
These two curated lists are complementary, with one focusing on tools for managing ML pipelines and the other on tools for monitoring the output of those pipelines.
About awesome-ml-pipelines
awesome-mlops/awesome-ml-pipelines
A curated list of awesome open source tools and commercial products that will help you manage machine learning and data-science workflows and pipelines 🚀
This is a curated collection of tools and products that help data scientists and machine learning engineers manage and automate their complex data and machine learning workflows. It provides options for orchestrating tasks, scheduling jobs, and monitoring the entire lifecycle of a machine learning project, from data ingestion to model deployment. The resources help you build robust, repeatable, and scalable machine learning pipelines.
About awesome-ml-monitoring
awesome-mlops/awesome-ml-monitoring
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
Staying on top of your machine learning models' performance and the quality of data feeding them is crucial after they've been deployed. This project provides a curated list of tools that help you monitor your ML models and data, identify issues like data drift or model decay, and get insights into why they might be underperforming. Data scientists, MLOps engineers, and analytics professionals will find this useful for maintaining healthy ML systems.
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